One challenge to obtaining high data transmission rates in Code Division Multiple Access (CDMA) systems, such as Wideband CDMA and IS-2000, is interference due to channel dispersion. Performance in CDMA systems is sensitive to multi-path dispersion when a low spreading factor and/or multi-code is used for transmitting data. With dispersion, there are multiple echoes of the transmitted signal with different relative delays. These echoes interfere with one another. Not only is orthogonality lost between successive symbols as one symbol overlaps with the next, but orthogonality is also lost between symbols sent on different, orthogonal codes.
Generalized RAKE (GRAKE) receivers have been developed for better suppressing interference. Interference suppression is achieved by treating Intersymbol Interference (ISI) and Multiple Access Interference (MAI) as colored Gaussian noise. The noise correlation across fingers is then exploited by adapting the finger delays and combining weights. In this way, the orthogonality between user signals may be partially restored. Recently, further improvements in GRAKE receivers have been proposed for the High Speed Downlink Packet Access (HSDPA) mode of WCDMA that take into account code cross correlations.
Multi-user detection techniques have also been used to suppress MAI and ISI due to channel dispersion. Various types of multi-user detectors are known. The optimal multi-user detector is a Maximum Likelihood Sequence Estimation (MLSE) detector. However, the complexity of an MLSE detector grows exponentially with the number of users and is therefore not practical to implement. Therefore, there is interest in developing suboptimal detectors that obtain good performance with low complexity.
One suboptimal multiuser detector is the linear minimum mean squared error (LMMSE) detector. However, the MMSE detector has a number of drawbacks. One drawback is the need to know all of the active codes. This requirement is not a problem for a base station, but is difficult to achieve for a mobile terminal. Another drawback to a conventional MMSE approach is the need to perform matrix inversion to estimate symbols. The matrix inversion operations make computations difficult in some circumstances.